feat: per-POV summary and edge summary update on scene close

chat/web/drawer.py

@@ -32,11 +32,13 @@ from fastapi.responses import HTMLResponse
 from fastapi.templating import Jinja2Templates
 
 from chat.eventlog.log import append_and_apply
+from chat.services.scene_summarize import apply_scene_close_summary
 from chat.state.edges import get_edge
 from chat.state.entities import get_bot, get_you
 from chat.state.memory import get_pinned
 from chat.state.world import active_scene, get_activity, get_chat, get_container
 from chat.web.bots import get_conn
+from chat.web.kickoff import get_llm_client
 
 TEMPLATES = Jinja2Templates(
     directory=str(Path(__file__).resolve().parent.parent / "templates")
@@ -143,13 +145,17 @@ async def close_scene_manual(
     chat_id: str,
     request: Request,
     conn=Depends(get_conn),
+    client=Depends(get_llm_client),
 ):
     """Manual scene close from the drawer button.
 
     Always available when there's an active scene; mirrors the auto-close
-    path in the turn flow but bypasses the classifier. Returns the refreshed
-    drawer partial so HTMX swaps it in. ``400`` when no scene is active —
-    the button is hidden in that state but a stale tab might still POST.
+    path in the turn flow but bypasses the hard-signal classifier. After
+    emitting ``scene_closed`` we run the T27 per-POV summary pipeline
+    (one classifier call) so the manual path produces the same memory /
+    edge updates as the auto path. Returns the refreshed drawer partial
+    so HTMX swaps it in. ``400`` when no scene is active — the button is
+    hidden in that state but a stale tab might still POST.
     """
     chat = get_chat(conn, chat_id)
     if chat is None:
@@ -167,11 +173,22 @@ async def close_scene_manual(
         payload={
             "scene_id": scene["id"],
             "ended_at": chat.get("time"),
-            # T27 will set this from the per-POV summary pass; for T26 we
-            # default to 0 so the projector update has a value to write.
+            # Significance defaults to 0; T22's significance worker
+            # operates on memories, not scenes.
             "significance": 0,
         },
     )
+
+    settings = request.app.state.settings
+    await apply_scene_close_summary(
+        conn,
+        client,
+        classifier_model=settings.classifier_model,
+        chat_id=chat_id,
+        scene_id=scene["id"],
+        host_bot_id=chat["host_bot_id"],
+        timeout_s=settings.classifier_timeout_s,
+    )
     return await drawer(chat_id, request, conn)